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Progress report
Geographies of conservation II:
Technology, surveillance and
conservation by algorithm
William M. Adams
University of Cambridge, UK
Abstract
The wide range of wildlife tracking and surveillance technologies (radio and satellite tracking, cameras, and
audio) that are being deployed in conservation have important implications for a geographical understanding
of care for non-human nature. This report explores four dimensions of their influence. First, their detailed
view of spatial dimensions of non-human lives affects conservation’s demarcation and control of space.
Second, the application of surveillance technologies to people is central to the rise of coercive conservation
strategies. Third, such technologies enable the creation and commoditization of spectacular nature. Fourth,
spatial digital data enables the automation of conservation decisions, a trend described here as ‘conservation
by algorithm’.
Keywords
animal geographies, camera traps, coercive conservation, conservation, conservation by algorithm, drones,
radio-tracking, spectacle, surveillance, technologies, tracking
She lived her life under near constant surveillance
and was continually stressed by the interactions
with the human world. She was tracked and
logged as data. ...We’re watching her. She’s
watching us. And at the same time, we’re watch-
ing ourselves. (Mendez and Allison (2012) Bear
71. National Film Board of Canada)
I Introduction
On 2 May 2009, scientists from the British Trust
for Ornithology (BTO) and the Swiss Ornitho-
logical Institute caught a nightingale in a mist
net on the eastern edge of the Cambridgeshire
Fens, UK. A tiny electronic ‘geolocator’ tag was
attached to its back, and the bird was released. A
year later, it was recaptured in the same place
and the tag was removed (BTO, 2016).
A geolocator consists of a battery, a light
sensor, a clock and a chip. By recording light
levels over time, it is possible to calculate lati-
tude and longitude, and hence the bird’s loca-
tion. The tag recorded the nightingale’s autumn
migration to Africa, via the Pyrenees, Madrid
and Lisbon to Senegal and Guinea. Somehow it
made its way back, although the route was not
recorded (BTO, 2016).
The nightingale, a bird laden with cultural
associations (Mabey, 1993), declined in num-
bers in the UK by 91 per cent between 1967 and
2007 (Holt et al., 2012). Many long-distance
Corresponding author:
William M. Adams, Department of Geography, University
of Cambridge, Downing Place, Cambridge CB2 3EN, UK.
Email: wa12@cam.ac.uk
Progress in Human Geography
1–14
ªThe Author(s) 2017
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DOI: 10.1177/0309132517740220
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migratory species are in decline, making them
an urgent conservation priority internationally
(Wilcove and Wikelsky, 2008; CMS, 2014).
Effective conservation of such species is seen
to demand better understanding of conditions on
migration routes to target conservation action
(Vickery et al., 2014; Marek, 2017; Hewson
et al., 2016). It is to this end that the Cambridge-
shire nightingale carried its geolocator to
Africa.
In the last two decades, movement ecology
has made significant contributions to conserva-
tion (Benson, 2016), supplying novel data used
to increase the effectiveness of conservation
action (Verma et al., 2016). Devices such as
geolocators represent just part of a wider digital
reshaping of conservation ideas and practice,
involving monitoring, public engagement, citi-
zen science, data analysis, and decision-support
(Arts et al., 2015, Van der Wal and Arts, 2015,
Verma et al., 2016). Computer and communica-
tion technologies such as low-cost sensors,
smartphone ‘apps’, and the predictive analytics
of ‘big data’ analysis are transforming biologi-
cal field recording (August et al., 2015). Con-
servation organizations have been leading users
of such technology, in pursuit of more robust
and evidence-based conservation decisions
(Sutherland et al., 2004; Adams and Sandbrook,
2013) and stronger public engagement and
support.
The development and adoption of digital
tracking and surveillance technologies in con-
servation have significance for human geogra-
phers interested in conservation in a range of
ways. This report explores four of these: first,
the implications of spatial data on animal move-
ments for conservation’s demarcation and con-
trol of space; second, the role of surveillance
technology in the rise of coercive conservation
strategies; third, the role of technology in the
creation and commoditization of nature specta-
cles; fourth, the way in which digital data
enables and encourages the automation of con-
servation decisions, a trend described here as
‘conservation by algorithm’. Before this discus-
sion, the report locates the role of technology as
part of conservation’s biopolitical regime, and
sketches the range of tracking and surveillance
technologies being deployed.
II Technologies of tracking
and surveillance
There is an irony, perhaps, in the way in which
the conservation of ‘nature’ requires the embed-
ding of technology such as a geolocator among
the feathers of a nightingale. Yet this harnessing
of technology should come as no surprise.
Whatever its diversity of ideology and concern
(Sandbrook, 2015a), biodiversity conservation
is a biopolitical regime, a form of governance
whose aim is ‘to secure the future of a valued
life (both human and nonhuman) at the scale of
the population’ (Lorimer, 2015: 12). Conserva-
tion involves the exercise of power over both
nature (keeping species and ecosystems within
specific bounds in terms of state and location)
and humans (determining who may take, kill or
transform non-human lives and spaces). Tech-
nology is central to conservation’s exercise of
biopower, marshalling the ‘productive and
destructive processes through which life is
made to live or left to die’ (Lorimer, 2015: 13).
In biodiversity conservation, humans have in
effect become ‘curators of wildlife’ (Verma
et al., 2016: 77). Classic ‘command and control’
conservation (Holling and Meffe, 1996) bor-
rows techniques, skills and devices from other
kinds of more-than-human biopolitical manage-
ment (hunting, fishing, forestry, disease or pest
control; Lorimer, 2015). In its locally intensive
policing of nature, conservation routinely cuts,
burns, poisons, shoots and traps (Woodworth,
2013), seeking to establish or enhance species
here (those characteristic or in decline) and con-
trol or extirpate others elsewhere (especially
those classed as ‘alien invasive species’; Pearce,
2015; cf. Hobbs et al., 2013). In its deployment
of technologies of control, conservation draws
2Progress in Human Geography XX(X)
on longstanding science-based modes of under-
standing nature, including its own academic dis-
ciples in game management (Leopold, 1933) or
the bespoke missionary field of conservation
biology (Meine et al., 2005).
Technologies that extend the capacity of
humans to observe and record the presence of
other organisms act essentially as prosthetic
devices that extend human abilities to perceive
and observe other lives (Lorimer, 2007, 2015).
Key technologies in terms of geographies of
conservation are those that allow individual
organisms to be identified at particular locations
and times. Such tracking and surveillance
devices can be thought of in two categories:
first, those attached to individual animals, and
second, those that are remotely deployed.
In terms of animal-borne devices, the oldest
is probably bird ringing (or banding, USA),
developed at the end of the 19th century, which
consists of attaching a unique numbered metal
ring to the leg of a captured wild bird, in the
hope that this will be returned when the bird is
killed or recaptured (Robin, 2001; Bircham,
2007). Techniques were developed to identify
individuals visually, for example the use of bird
rings of different colours, or, for other taxa,
visible marks or tags attached to ears, flippers
or fins.
The invention of transistors in 1947 revolu-
tionized the tracking of wild animals (Benson,
2010). The development of radio telemetry in
the USA in the 1950s benefitted from close Cold
War links to military scientific networks, tech-
nology and funding (Benson, 2010). It began to
be routine to attach transmitters whose unique
radio signal could be detected by fixed or mova-
ble aerials, to collars or harnesses (mammals
and birds), or by suckers or darts into the body
(e.g. fish and marine mammals).
Since the 1950s, radio telemetry devices have
grown steadily smaller and more powerful, with
improved battery life. Detection has become
possible from greater distances, from aircraft,
helicopters and even satellites (Pennisi, 2011).
GSM mobile phone technology allows location
to be captured continuously via a mobile phone
network, giving advantages in terms of spatial
accuracy (a few metres), size, cost and battery
life (e.g. Graham et al., 2009). Miniaturized sat-
ellite tags weighing below 5 g can be fitted to
birds such as turtledoves and cuckoos weighing
as little as 100 g (Hewson et al., 2016). Tags as
light as 1.6 g have now been developed (Marek,
2017). Digital data on animal movement is
widely collected, and increasingly it is shared
in standardized format through centralized
open-access archives such as Movebank
(https://www.movebank.org/).
Digital technologies have also revolutionized
remote surveillance. Remote sensing platforms
and sensors have evolved continuously and
become standard conservation tools. Panchro-
matic (black and white) photography from bal-
loons and aeroplanes was developed for military
use in the First World War, and transformed by
stereo photography in the second. Post-war, col-
our photography, and film stock sensitive out-
side the visible spectrum (e.g. infrared) began to
be used for land systems and ecological map-
ping. From the 1970s, multispectral digital ima-
ging from satellite sensors provided civilian
environmental scientists with relatively afford-
able and frequent-repeat imagery of much of the
earth’s surface within and beyond the human
visual spectrum. This made continental scale
ecological mapping possible. Such images and
data are now widely available for download
from the internet.
Semi-automated mapping of vegetation and
other natural features was made possible by
computerized data and analysis. Geographical
information systems allowed data derived from
various sources to be superimposed and the
resulting maps analysed, published and dissemi-
nated. Recently, drones, or unmanned (sic) aer-
ial vehicles (UAVs), have brought the cost of
such surveillance down dramatically, broaden-
ing its accessibility, and triggering numerous
experiments in ecology and environmental
Adams 3
science (Anderson and Gaston, 2013). Satellite
and airborne radar provide other forms of data
which can also be integrated into conservation
assessments, for example LIDAR mapping of
the topography of forest canopies, and associ-
ated estimates of vegetation density, and hence
biomass, and therefore stocks of carbon relevant
to carbon offsetting schemes (Asner et al., 2010;
Simonson et al., 2012).
Remote photographic surveillance of indi-
vidual organisms has also been transformed
by digital technology. Animal photography
with automatically triggered camera flashes
was pioneered at the end of the 19th century
(Shiras, 1936). Technological advances
included the replacement of cumbersome
plate cameras with film, and from the
1930s small cameras using 35 mm cinema
film stock. The 1980s saw the development
of infrared motion detection, and the 1990s
the development of digital images. Camera
traps are widely used in wildlife biology
(Ancrenaz et al., 2012; O’Connell et al.,
2011; McCallum, 2013), many operating
beyond the human visual range (e.g. infrared).
Close-circuit video is also now commonly
deployed at conservation sites (Chambers,
2007; Verma et al., 2015, 2016).
Digital audio sensors allow animals to be
located and identified using sound, including
sound beyond the range of human hearing
(e.g. the ultrasonic calls of bats). Software
can identify and separate species automati-
cally (Robinson Willmott et al., 2015).
Sonic surveillance can also be conducted
underwater (e.g. passive acoustic tracking
of migrating humpback whales; Stanistreet
et al., 2013).
This quick sketch of technologies for animal
tracking and surveillance indicates their
extraordinary scope. The gaze of field biology,
and conservation, is not yet panoptic, but the
intent – and perhaps the capacity – is clear. Let
us turn to its significance for geographies of
conservation.
III Surveillance and conservation
geographies
The first important aspect of digital tracking and
surveillance technologies for geographies of
conservation lies in the levels of detail and inti-
macy of their view of non-human lives, and
their capacity to individuate, to isolate the
movement of the individual from the broad pat-
terns of the population. This has attracted the
attention of animal geographers (Hodgetts and
Lorimer, 2015; Buller, 2015). Thus Barua
(2014: 916) sees tracking technologies as cen-
tral to the development of ‘lively’ or ‘intradis-
ciplinary’ biogeographies, demonstrated by his
analysis of the ‘dwelt political ecology’ of ele-
phants among the forests and tea estates of
Assam. It is not just the geographies of animals,
but the geographies of particular animals, that
are opened to the scientific gaze. That gaze,
enabled by digital technologies, is inherently
spatial.
Digital tracking allows the construction of
‘wildlife cartographies’, mapping of species
distributions and using those representations
to enable ‘effective, targeted conservation
measures’ (Verma et al., 2016: 81). In particu-
lar, it provides the evidence base for territorial
claims in the form of new protected areas. Thus
Benson (2016) shows how animal tracking not
only changes understanding of the way the
individual animals and populations use land,
but also therefore conservation’s ability to
lay claim to that land. American wildlife
biologist Helmut Buechner studied Uganda
kob (an antelope) in the 1950s, using tranqui-
lizing darts and drugs, plastic collars, identify-
ing tags, and moving films. This ‘spatial-
biopolitical expertise’ (Benson, 2015: 138)
allowed him to demonstrate the territorial
behaviour of the kob, and convert this into a
conservation argument about the need for pro-
tected areas. The ‘territorial claims of endan-
gered species’ could therefore be pressed in
the face of competing land use demands,
4Progress in Human Geography XX(X)
legitimated by other kinds of colonial scientific
expertise (Benson, 2016: 137).
Surveillance not only intensifies conserva-
tion territorialization in terms of the demarca-
tion of spaces for nature and for people, but also
the management of the resulting boundaries. If
animals can be tracked, their boundary-
crossings become not only something that can
be, but must be, managed, as for example when
elephants with GPS collars cross virtual ‘geo-
fences’ in the landscape to engage in crop raid-
ing, or break electric fences built to protect
smallholder farms (Graham et al., 2010; Evans
and Adams, 2016). Tagged animals can be seen
by the public as the responsibility of those who
know their movements, and can be at risk when
they move close to people (Cooke et al., 2017).
Thus an endangered great white shark killed in
Western Australia because it was judged an
‘imminent threat’ to a bathing beach was only
known to be present because of an acoustic tag
fitted by scientists (Meeuwig et al., 2015).
The ability to track also influences conserva-
tion in its selection of priorities for action. Con-
servation organizations actively select
charismatic species (cf. Lorimer, 2007) as flag-
ships for technological projects. Focal species
are selected to be ‘easily recognisable, predict-
able, detectable, distinctive, larger, and yet
unique’ (Verma et al., 2015: 657). The ‘track-
ability’ of a species therefore influences its vis-
ibility in conservation strategies (Benson, 2016:
143), although some megafauna such as ele-
phants offer both traditional photogenic char-
isma and trackability (Graham et al., 2009;
Barua, 2016; Benson, 2016).
IV Surveillance and coercive
conservation
A second implication of tracking and surveil-
lance technologies for geographies of conserva-
tion is their role in the development of coercive
conservation strategies (Peluso, 1993). People
as well as other animals can be subjected to
surveillance and control measures. Digital
sensing and tracking devices (camera traps,
drones and satellites) are widely used to monitor
human activities for conservation law enforce-
ment (e.g. to monitor illegal logging or poach-
ing, collect evidence or catch perpetrators;
Humle et al., 2014; Sandbrook, 2015b).
However, the use of surveillance technology
in conservation has outstripped institutional fra-
meworks for its governance – for example, little
attention has been paid to the social risks of
conservation drones (Sandbrook, 2015b).
Furthermore, surveillance technology is funda-
mental to the militarization of conservation,
such as Africa’s ‘war on poaching’ (Duffy,
2000, 2014; Neumann, 2004), ‘green militariza-
tion’ (Lunstrum, 2014), or ‘green violence’
(Bu
¨scher and Ramutsindela, 2015). A discourse
of ‘poachers-as-terrorists’ in Africa has made
illegal hunters legitimate targets for counter-
insurgency violence. Surveillance technologies
such as camera traps, drones, helicopter-
mounted infrared cameras and sniper rifle night
sights are routinely used to combat poachers in
Kenya (Haslam, 2016). The WorldWide Fund
for Nature has collaborated with Google.org to
develop a thermal and infrared camera and soft-
ware system to detect people crossing a national
park boundary (WWF, 2017). The ease with
which technologies can be re-targeted between
animals and people, and between warfare and
securitized conservation, is an important dimen-
sion of the prosecution of ‘war by conservation’,
in which conservation is drawn into a globalized
security agenda (Duffy, 2016).
Conservation surveillance uses fear as a tool
(Humle et al., 2014) to enforce environmental-
ity on reluctant rural people (Agrawal, 2005).
Such surveillance, and the sometimes-violent
enforcement linked to it, offers the same chal-
lenges to rights and liberties as drones in the
service of state security and warfare. It brings
about what Shaw (2017: 9) calls ‘atmospheric
enclosure’, creating ‘biopolitical climates for
human beings to dwell inside’. Shaw’s focus
Adams 5
is urban policing, but the skies are also increas-
ingly threatening in conservation areas, both
surveillant and even potentially directly
weaponized.
To balance the growing evidence of the
deployment of surveillant technology against
citizens, it might be noted that digital technol-
ogy can also be used by those disadvantaged by
conservation territorialization and boundary-
making. There is no reason (beyond cost and
access) why technologies such as drones should
not be used by communities in counter-mapping
(Peluso, 1995). Butt (2015) describes how
mobile phones help herders in Tanzania to sub-
vert ‘ever-tightening restrictions on access to
land’, sending warnings of the presence of game
guards to enable grazing in areas incorporated
into protected areas. Graham et al. (2012)
describe the use of mobile phones by small-
holder farmers to inform state wildlife managers
when elephants cross the boundaries of wildlife
conservancies and other areas where they are
tolerated to raid growing crops.
V Surveillance, spectacle and
commodity
The third aspect of tracking and surveillance
technologies to which I want to draw attention
is their capacity to create a spectacle of non-
human lives (Igoe, 2010; Igoe et al., 2010).
Spectacular nature has long been a commercial
product, and one widely deployed by conserva-
tionists. The intimate gaze of the camera has
been a feature of wildlife film and television
since the 1930s (Mitman, 1999; Lorimer,
2015), and technology continues to extend its
scope: the 2017 BBC wildlife blockbuster Pla-
net Earth II drew heavily on the novelty of digi-
tal trail cameras, night vision photography and
drones to provide its ‘high-dose nature therapy’
(Rose, 2017).
Digital technologies are fundamental to the
work that conservation does to frame affective
relations between people and non-human
nature. Close-circuit television (CCTV, or the
‘wildlife-cam’) has become a routine adjunct of
visitor experience at conservation sites and
online (Chambers, 2007; Verma et al., 2015).
Cameras positioned at the nests of rare birds
such as peregrine falcons (e.g. Derby Pere-
grines, 2017) or by an African stream (e.g.
Explore, 2017) and linked to the web provide
continuous streaming of ‘live’ images. Conser-
vation organizations routinely use CCTV to
capture interest, and create emotional ‘connec-
tion’ with members of the public (Verma et al.,
2015), to educate, create the sense of the need
for care, and to generate financial and other
forms of support.
CCTV and wildlife film appear to offer an
unedited view of the life of wild animals, free
from human ‘intrusion’ (Verma et al., 2015).
Yet the sense of proximity relies on a physical
and technological separation between watchers
and watched, creating a complex hybrid of real
and virtual. CCTV transforms animal bodies
into digital images that can be stored (and can
be re-run as ‘highlights’), and restricts sensory
interactions to the visual (there are no ‘live’
smells or noises). This makes ‘CCTV-assisted
bird watching’ and similar spectacles paradoxi-
cally geographically distancing (Chambers,
2007). Digital video epitomizes ‘technological
nature’, mediating, augmenting and simulating
physical nature (Kahn, 2009). Virtual natures
are increasingly pervasive, (for example in con-
servation games; Sandbrook et al. 2014;
Dorward et al., 2016). Some fear that the lure
of virtual nature (particularly to young people)
will erode authentic experiences of non-human
nature (e.g. Louv, 2005; Ellard, 2015).
At the same time, footage from wildlife cams
does not always invoke passivity in viewers.
Verma et al. (2015) record the highly emotional
responses of people viewing webcams (for
example a peregrine falcon trying to feed a dead
chick), and Brulliard (2016) reports aggressive
response of American viewers watching star-
ving chicks on nest cams of birds of prey.
6Progress in Human Geography XX(X)
Bu
¨scher (2015) notes how viewers of wildlife
cams in South Africa used social media to
demand intervention by conservation managers,
for example if an animal appeared injured.
Tracking technologies also create new possi-
bilities for the creation of spectacle, and facil-
itate new networks of care, based on the
identification of individual animals. Thus in
Scotland, the locations of satellite tagged red
kites were combined with other data to create
a weekly ‘blog’ describing the movements of
four birds on a ‘BloggingBirds’ website, using
natural language technology (http://redkite.abd
n.ac.uk; Van der Wal et al., 2015). Similarly, the
British Trust for Ornithology publishes the loca-
tions of satellite tagged cuckoos on their migra-
tion to Africa to publicize their scientific work
and the challenges of cuckoo conservation
(Verma et al., 2016).
Spectacular images of nature have every-
where become an indispensable part of conser-
vation’s engagement with capitalism (Igoe,
2010; Igoe et al., 2010). Corporate brands are
linked to conservation causes, using ‘images of
landscapes, exotic people and animals to raise
financial support for conservation interven-
tions’ (Igoe, 2010: 378). Thus, in the case of the
BTO’s tagged cuckoos, an attempt has been
made to monetize these data streams through
sponsorship. The BTO website offered the
opportunity to ‘sponsor a cuckoo’ (BTO,
2017) in return for an information pack, a choice
of gift item, regular email updates on the cuck-
oos and their name on a list of sponsors.
As conservation increasingly embraces
market-based models, nature that is threatened
or saved is alike represented in ‘dramatic, tech-
nologically mediated and circulated perfor-
mances’ (Sullivan, 2012: 202). Conceptual
devices used to stabilize, monetize and market
non-human nature (such as carbon credits or
biodiversity offsets) depend on spectacular digi-
tal representations of nature as ‘products’ that
can be bought and sold (Sullivan, 2012, 2013).
Social media create and circulate ‘new virtual
forms and manifestations of nature and its
conservation’ (Bu
¨scher, 2013: 1). In ‘Nature
2.0’ applications, nature is increasingly to be
‘“saved” through mouse-clicks and double-
taps’ (Bu
¨scher, 2016: 727). Surveillance and
spectacle are respectively the preferred method
and core product of global conservation.
VI Conservation by algorithm
The fourth and final aspect of digital tracking
and surveillance technology to which I wish to
draw attention is its role in the automation of
conservation decisions. Digital devices, espe-
cially using online or mobile phone-based inter-
faces (August et al., 2015; Teacher et al., 2013;
Van der Wal et al., 2016), are transforming the
field collection of biological data. These tech-
nologies generate more, better, faster and
cheaper data capture from sensors, with contin-
uous and geographically located data over a
larger spatial extent and in previously inacces-
sible locations (Arts et al., 2015). Digital track-
ing and surveillance sensors bring advantages of
continuous flows of data, lower costs of capture,
reduced costs in data transfer and storage in
shared multi-species databases (Benson,
2016). However, perhaps the greatest signifi-
cance of digital technologies lies in the ease
with which data can be fed directly into compu-
tational algorithms. As Joppa (2015: 525)
observes, the way in which computational tech-
nology provides ‘tools and infrastructure to
monitor, model, and safeguard biodiversity in
entirely new ways’ is starting to revolutionize
the practice of conservation.
Technical advance means that conservation
data collection is increasingly being automated,
bypassing (or making redundant) scientifically
skilled conservation workers. Fixed sensors can
record continuously and download data without
human intervention. Automation also allows
new kinds of data to be recorded. For example,
algorithms can automatically identify individ-
ual tigers from stripe patterns on photographs
Adams 7
(e.g. Yu et al., 2013) and distinguish different
species of bats from the characteristics of their
ultrasonic calls from continuous digital record-
ings, an impossibly daunting task for human
analysis (Adams et al., 2010).
Computer-aided taxonomy enables reliable
biological data to be derived from the observa-
tions of even unskilled citizens. In the Google
Play store, Jepson and Ladle (2015) find numer-
ous apps for automated species identification,
for example automated acoustic species detec-
tion and identification, and the use of image
recognition software to automatically identify
tree species from their leaves. Data quality from
citizen observers can be improved by automated
feedback (Van der Wal et al., 2016). The eBird
website (http://ebird.org/) converts observa-
tions by amateur ornithologists into a centra-
lized database usable by scientists (Wood
et al., 2011).
People can also be made to provide data of
conservation importance unconsciously,
scraped from social media or recorded by spe-
cialized apps. For example, Google Trends data
can track natural events such as the flowering of
asthma-producing plants, or the occurrence of
biting insect species (Proulx et al., 2013), and
data on the health and mood of smartphone
users can be linked to location to analyse how
people interact with nature and protected areas
(Teacher et al., 2013).
Not only data collection but also data clean-
ing can be automated. Modelling techniques
from engineering and computer science are
being applied in ecology to perform quality con-
trol procedures to filter out erroneous data
(Porter et al., 2012). Swinnen et al. (2014)
describe an automated processing protocol to
sort video recordings from trail cameras, set to
record beavers, that were empty, or recorded
other species, without having to watch the
recordings. Price-Tack et al. (2016) have devel-
oped automated image processing to identify
animal presence in time-lapse camera trap
images, reducing personnel time and costs.
In part, the automation of analysis is an inev-
itable concomitant of the deployment of digital
sensors (what Gregory (2011: 194), in the con-
text of drone warfare, describes as the ‘image
surge’). The volume and rate of flow of data
from environmental sensor networks are chal-
lenging traditional systems of data management
(e.g. transport, storage, quality control and
assurance, gap filling and analysis), and driving
a new field of ecological informatics or ecoin-
formatics (Porter et al., 2012). As in the drone
warfare, automated software systems are
required to analyse data streams to identify sig-
nificant patterns (cf. Gregory, 2011). Auto-
mated analysis of surveillance data for
conservation is becoming feasible in real time.
Thus Robinson Willmott et al. (2015) describe a
novel system of linked thermal, acoustic and
ultrasound sensors to monitor bird and bat
movements in the eastern USA, with a view to
temporary shut-downs of wind turbines to
reduce mortality from collisions.
Digital tracking and surveillance technolo-
gies are important elements in automated anal-
ysis and planning in conservation.
Automatically cleaned and checked data are
transferred to information management systems
where scientific workflows provide quality
assurance and additional metadata, before anal-
ysis (Porter et al., 2012). Digital data fed
directly into algorithms and models (Benson,
2016) in turn support conservation decisions
and policy prescriptions.
Increasing dependence on digital tracking
and surveillance can therefore be seen as a new
conservation regime, one of ‘conservation by
algorithm’. In security and military contexts,
digital data are routinely handled by algorithm,
translating probable associations between peo-
ple into ‘actionable security decisions’
(Amoore, 2009). Drone killing involves the
deployment of autonomous algorithms that
automate target recognition (Allinson, 2015).
Algorithmic rules of association have become
the basis for everyday securitization in what
8Progress in Human Geography XX(X)
Amoore (2009) calls ‘algorithmic war’. Conser-
vation applications are therefore quickly fol-
lowing models that eerily copy the automated
military kill chain. Thus a wildlife concession in
Tanzania uses a reconnaissance drone fitted
with photographic recognition software ‘to pick
up and differentiate potential threats like poa-
chers and cattle from naturally occurring objects
[sic] like wildlife’. If a potential threat is iden-
tified, an ‘ops room technician’ reviews the foo-
tage and any threat is registered in the
computerized Domain Awareness System
(DAS) and ‘law enforcement assets are imme-
diately dispatched to deal with the problem’
(Singita Grumeti Fund, 2017).
Algorithms are as yet mostly having subtler
effects in conservation. But there are nonethe-
less implications. While digital data collection
may be distributed among a range of actors
(even, potentially, shared with local people),
conservation planning and decisions based on
digital data streams tend to be concentrated in
the hands of experts, remote from the field, in
the offices of government, academic or non-
governmental organizations (cf. Bryant, 2002;
Fairhead and Leach, 2003). Advances in remote
sensing, machine-based mapping and spatial
analysis are fundamental to spatial conservation
planning (Moilanen and Wilson, 2009) and the
field of ‘conservation biogeography’ (Richard-
son and Whittaker, 2010; Ladle and Whittaker,
2012). Applications range from the prioritiza-
tion of law enforcement effort using data on the
spatial distribution of illegal activities (Plump-
tre et al., 2014) to the classification of land in
terms of conservation importance and priority
for protection, at any scale from local to global
(e.g. Brooks et al., 2006). Site selection and
decision-support algorithms identify areas that
have the potential to maximize the achievement
of conservation goals, whilst minimizing
resources expended (Fajardo et al., 2014).
Of course, such as their name suggests,
decision-support tools are supposed to inform
and enable a planning system run by human
decision-makers. Yet automation tools are
increasingly mainstream. Thus the NatureServe
network offers a range of specialized conserva-
tion planning tools and models such as ‘Natur-
eServe Vista’ (‘A Powerful Scenario-Based
Assessment and Planning Tool’), which can
‘automate complex GIS processes, keep track
of your work, and deliver defensible, repeatable
maps and reports’ (NatureServe, 2017). The
deployment of such tools moves conservation
decisions further away from people affected
by them and further into the hands of remote
decision-makers, or the technicians who devise
the algorithms on which they rely. Algorithmic
conservation involves a biopolitical regime
operated remotely and autonomously that sub-
jects both nature and society to discipline.
VII Conclusion
Tracking and surveillance technologies are
shaping conservation in a range of ways of
importance to geographers. They offer radical
new insights into non-human lives, enabling and
stimulating new regimes of management and
control. They enable and justify coercion as a
way of addressing conservation problems such
as poaching, drawing on military methods,
machines and mind-sets to change the balance
of power in and around conservation zones.
They offer new forms of spectacular nature, and
new opportunities to monetize those data streams
and interact with potential conservation support-
ers on the cusp between the virtual and physical
world. Finally, they are a key part of the growing
trend towards conservation by algorithm, where
conservation decisions are automated and not
tested through political debate.
Lorimer (2015) explores the possibility of
conservation based on a more ‘cosmopolitical’
cohabitation with nature. But biodiversity con-
servation, increasingly scientific in method and
neoliberal in ideology and structure (Brocking-
ton and Duffy, 2010; Bu
¨scher et al., 2012), is
in many ways becoming less open and
Adams 9
collaborative than Lorimer would wish. Conser-
vation is a major beneficiary of the bulked out
analytical power offered by tracking and sur-
veillance technologies. These make it possible
to address novel conservation problems, for
example the protection of species migrating
between regions and environments, or those
experiencing range shifts due to climate change.
Yet the rise of algorithmic conservation
could bring about profound change. To take just
one rather wild example, Cantrell et al. (2017:
156) explore the potential for ‘the automated
curation of wild places’. They offer a concep-
tual design for a ‘wildness creator’, a fully auto-
mated and autonomous artificially intelligent
infrastructure system ‘to create and sustain
non-human wildness without the need for con-
tinuing human intervention’ (Cantrell et al.,
2017: 161).
Tracking and surveillance technologies, and
digital technologies more widely, have real
implications for the social, political and envi-
ronmental impacts of conservation. With
advances in technology, reductions in cost,
increases in the volume and diversity of data
that can be collected and the range of algorithms
that can be applied to it, conservation decisions
increasingly move into the hands of experts and
away from democratic oversight. The politics of
future conservation geographies is increasingly
shaped by technologies and algorithms. The
question of who owns, programmes and con-
trols them is of crucial importance.
Acknowledgements
My thanks to everyone at the Division of History of
Science, Technology and Environment at KTH,
where this report was first drafted, to Chris Sand-
brook for comments on the manuscript and to him
and Kent Redford for many conversations about con-
servation technologies.
Declaration of conflicting interests
The author(s) declared no potential conflicts of inter-
est with respect to the research, authorship, and/or
publication of this article.
Funding
The author(s) received no financial support for the
research, authorship, and/or publication of this
article.
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